Online Auction-Based Resource Allocation for Service-Oriented Network Slicing

Abstract

Future mobile communication networks (5G) are envisioned to support a wide range of use cases with diverse service requirements. Network slicing as a key architectural enabling technology for 5G can provide users with customized services and meet the requirement of economic efficiency, where resource allocation is of vital importance. In this paper, we propose an online auction-based resource allocation scheme for network slicing (ORANS) to meet the diverse service requirements and improve network economic efficiency. We first propose a bidding information construction method to provide customized bidding information for users based on service types. Next, we model the slicing resource allocation problem as an online winner determination problem, with aim to maximize the social welfare of auction participants. We then implement a resource allocation strategy and payment rule to accomplish the service-oriented optimal resource allocation. Extensive simulation experiments are conducted to evaluate the performance of the proposed ORANS and the numerical results show that ORANS significantly outperforms the greedy algorithm and the primal-dual approximation algorithm in network economic efficiency while satisfying the diverse service requirements of users.